Do Children’s “Best Interests” Matter When Tracing Their Filiation in Quebec Civil Law ?
Bibliographic record
Abstract
This essay offers a commentary on the intersection between the best interests principle and the law of filiation in Quebec. It highlights the tension between best interests and the positive law of filiation, highlighting the implications for those most vulnerable in family law disputes who have been central to Professor Goubau’s scholarship. The analysis here is premised on a review of four relatively recent decisions handed down by Quebec courts, each distinct in its context. The first considers circumstances of assisted procreation or “parental projects” that result in more than two prospective parents ; the second addresses intercultural adoption contexts ; the third examines determinations of filiation where a child’s birth ensues from a surrogacy agreement ; and the fourth explores how the law deals with stepparent-stepchild relationships. In each context, a judgment is featured to explore how the law intersects with the best interests principle. While none of the judgments are intended to be representative of the state of the law in a given area, each offers an example to illustrate how courts negotiate tensions between the positive law and the best interests principle. While judges will have varying degrees of discretion in different contexts to consider this principle, they acknowledge the tension and seek to reconcile it in a manner that at once foregrounds children’s interests while also correctly applying and interpreting relevant legal authorities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.020 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".